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Biology subjects

Simic, M. S.

Publications and source records attributed to Simic, M. S..

3 recordsLinked to original sources

Spike-in probe-enhanced single-cell RNA-seq reveals post-infusion transcriptomic remodeling of "prime-and-kill" synNotch-CAR-T cells

We previously developed synthetic Notch (synNotch)-chimeric antigen receptor (CAR)-T cells to improve the safety and efficacy of CAR-T therapy for glioblastoma. In this system, an anti-EphA2/IL13R2-dual-CAR is expressed only upon recognition of tumor- or brain-specific "priming" antigens, EGFRvIII (termed E-SYNC cells) or brevican (B-SYNC), respectively, with E-SYNC currently under phase I clinical evaluation (NCT06186401). However, tracking and profiling these engineered cells in vivo remain challenging, limiting our understanding of their activity and therapeutic potential. To address this gap, we developed a single-cell RNA-sequencing (scRNA-seq) workflow with custom spike-in probes for synNotch-CAR transcripts, enabling simultaneous detection of engineered cells and transcriptomic profiling. In vitro, integration of multiple probes using machine-learning-assisted classifiers detected 78.2% of E-SYNC cells and 60.0% of B-SYNC cells with 98.0% specificity. In a xenograft model, synNotch-positive cells were detected across the spleen, lung, and brain, with the highest frequency and most robust priming and activation observed in the brain. Single-cell transcriptomic analyses revealed tissue-specific differentiation programs, including cytotoxicity, proliferation, metabolic activity, and acquisition of tissue-resident memory phenotypes, shaped by both environmental cues and synNotch-mediated antigen recognition. In summary, this spike-in probe-enhanced scRNA-seq workflow enables robust detection and high-resolution characterization of synNotch-CAR-T cell dynamics and provides a broadly applicable platform for monitoring engineered immune cells in diverse clinical contexts. One Sentence SummaryOur spike-in probe-enhanced single-cell RNA-sequencing method enables analysis of tissue-dependent activation and transcriptional states of synNotch-CAR-T cells, providing a robust and scalable platform for in vivo tracking and transcriptomic profiling of engineered cell therapies.

cancer biology↗

Exploring the rules of chimeric antigen receptor phenotypic output using combinatorial signaling motif libraries and machine learning

Chimeric antigen receptor (CAR) costimulatory domains steer the phenotypic output of therapeutic T cells. In most cases these domains are derived from native immune receptors, composed of signaling motif combinations selected by evolution. To explore if non-natural combinations of signaling motifs could drive novel cell fates of interest, we constructed a library of CARs containing [~]2,300 synthetic costimulatory domains, built from combinations of 13 peptide signaling motifs. The library produced CARs driving diverse fate outputs, which were sensitive to motif combinations and configurations. Neural networks trained to decode the combinatorial grammar of CAR signaling motifs allowed extraction of key design rules. For example, the non-native combination of TRAF- and PLC{gamma}1-binding motifs was found to simultaneously enhance cytotoxicity and stemness, a clinically desirable phenotype associated with effective and durable tumor killing. The neural network accurately predicts that addition of PLC{gamma}1-binding motifs improves this phenotype when combined with TRAF-binding motifs, but not when combined with other immune signaling motifs (e.g. PI3K-or Grb2-binding motifs). This work shows how libraries built from the minimal building blocks of signaling, combined with machine learning, can efficiently guide engineering of receptors with desired phenotypes. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=60 SRC="FIGDIR/small/474985v2_ufig1.gif" ALT="Figure 1"> View larger version (17K): org.highwire.dtl.DTLVardef@8dbf97org.highwire.dtl.DTLVardef@1d8300org.highwire.dtl.DTLVardef@1838ba0org.highwire.dtl.DTLVardef@143d907_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

Multi-antigen recognition circuits overcome challenges of specificity, heterogeneity, and durability in T cell therapy for glioblastoma

Treatment of solid cancers with chimeric antigen receptor (CAR) T cells is plagued by the lack of target antigens that are both tumor-specific and homogeneously expressed. We show that multiantigen prime-and-kill recognition circuits have the flexibility and precision to overcome these challenges in attacking glioblastoma. A synNotch receptor that recognizes a specific priming antigen - the heterogeneous glioblastoma neoantigen EGFRvIII or a brain tissue-specific antigen - is used to locally induce expression of a CAR, enabling thorough but controlled tumor killing by targeting of homogeneous antigens that are not absolutely tumor specific. Moreover, regulated CAR expression maintains a higher fraction of the T cells in the naive-like state which is associated with higher durability in vivo. In summary, using circuits that integrate recognition of multiple imperfect but complementary antigens, we improve the specificity and persistence of T cells directed against glioblastoma, providing a general recognition strategy applicable to other solid tumors.

immunology↗